Matches in SemOpenAlex for { <https://semopenalex.org/work/W4379212488> ?p ?o ?g. }
Showing items 1 to 63 of
63
with 100 items per page.
- W4379212488 abstract "Deep learning classifiers have demonstrated their ability to provide robust accuracy for the treatment of com- bined signals including electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS) [1], [2]. In this work, an evolutionary deep learning strategy is applied to classify different cognitive workload states that surgeons experience during laparoscopic surgery. The proposed learning strategy is applied to train an Evolutionary Multilayer Perceptron Neural Network (E- MLPNN), where multimodal raw data of EEG, fNIRS and Electrocardiogram (ECG) signals were collected and concatenated from a series of ten experiments using the back-end platform Multi-sensing AI Environment for Surgical Task & Role Optimisation (MAESTRO) as shown in Figure 1(a). Each experiment required surgical trainees to perform a simulated laparoscopic cholecystec- tomy (LCH), i.e. the removal of a gallbladder in a porcine model using a minimally invasive surgical technique as demonstrated in Figure 1(b). At each experiment, the level of Cognitive Workload (CWL) is assumed to increase as the mental activity increases during the surgical operation. As presented in Figure 1c, a number of tasks performed during the LCH were defined to measure the level of CWL" @default.
- W4379212488 created "2023-06-04" @default.
- W4379212488 creator A5004355689 @default.
- W4379212488 creator A5010907593 @default.
- W4379212488 creator A5024494145 @default.
- W4379212488 creator A5040195774 @default.
- W4379212488 date "2023-06-26" @default.
- W4379212488 modified "2023-10-01" @default.
- W4379212488 title "Evolutionary Deep Learning using hybrid EEG-fNIRS-ECG Signals to Cognitive Workload Classification in Laparoscopic Surgeries" @default.
- W4379212488 doi "https://doi.org/10.31256/hsmr2023.34" @default.
- W4379212488 hasPublicationYear "2023" @default.
- W4379212488 type Work @default.
- W4379212488 citedByCount "0" @default.
- W4379212488 crossrefType "proceedings-article" @default.
- W4379212488 hasAuthorship W4379212488A5004355689 @default.
- W4379212488 hasAuthorship W4379212488A5010907593 @default.
- W4379212488 hasAuthorship W4379212488A5024494145 @default.
- W4379212488 hasAuthorship W4379212488A5040195774 @default.
- W4379212488 hasBestOaLocation W43792124881 @default.
- W4379212488 hasConcept C108583219 @default.
- W4379212488 hasConcept C111919701 @default.
- W4379212488 hasConcept C119857082 @default.
- W4379212488 hasConcept C130796691 @default.
- W4379212488 hasConcept C153180895 @default.
- W4379212488 hasConcept C154945302 @default.
- W4379212488 hasConcept C15744967 @default.
- W4379212488 hasConcept C169760540 @default.
- W4379212488 hasConcept C169900460 @default.
- W4379212488 hasConcept C2778476105 @default.
- W4379212488 hasConcept C2781195155 @default.
- W4379212488 hasConcept C41008148 @default.
- W4379212488 hasConcept C522805319 @default.
- W4379212488 hasConcept C81363708 @default.
- W4379212488 hasConceptScore W4379212488C108583219 @default.
- W4379212488 hasConceptScore W4379212488C111919701 @default.
- W4379212488 hasConceptScore W4379212488C119857082 @default.
- W4379212488 hasConceptScore W4379212488C130796691 @default.
- W4379212488 hasConceptScore W4379212488C153180895 @default.
- W4379212488 hasConceptScore W4379212488C154945302 @default.
- W4379212488 hasConceptScore W4379212488C15744967 @default.
- W4379212488 hasConceptScore W4379212488C169760540 @default.
- W4379212488 hasConceptScore W4379212488C169900460 @default.
- W4379212488 hasConceptScore W4379212488C2778476105 @default.
- W4379212488 hasConceptScore W4379212488C2781195155 @default.
- W4379212488 hasConceptScore W4379212488C41008148 @default.
- W4379212488 hasConceptScore W4379212488C522805319 @default.
- W4379212488 hasConceptScore W4379212488C81363708 @default.
- W4379212488 hasLocation W43792124881 @default.
- W4379212488 hasOpenAccess W4379212488 @default.
- W4379212488 hasPrimaryLocation W43792124881 @default.
- W4379212488 hasRelatedWork W2731899572 @default.
- W4379212488 hasRelatedWork W2999805992 @default.
- W4379212488 hasRelatedWork W3116150086 @default.
- W4379212488 hasRelatedWork W3133861977 @default.
- W4379212488 hasRelatedWork W4200173597 @default.
- W4379212488 hasRelatedWork W4291897433 @default.
- W4379212488 hasRelatedWork W4300644791 @default.
- W4379212488 hasRelatedWork W4312417841 @default.
- W4379212488 hasRelatedWork W4321369474 @default.
- W4379212488 hasRelatedWork W4380075502 @default.
- W4379212488 isParatext "false" @default.
- W4379212488 isRetracted "false" @default.
- W4379212488 workType "article" @default.